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<table width="100%" summary="page for rain, wavesurge and portpirie"><tr><td>rain, wavesurge and portpirie</td><td style="text-align: right;">R Documentation</td></tr></table>

<h2>Rain, wavesurge, portpirie and nidd datasets.</h2>

<h3>Description</h3>

<p>Rainfall, wave-surge, Port Pirie and River Nidd data sets.
</p>


<h3>Format</h3>

<p>The format of the rain data is: num [1:17531] 0 2.3 1.3 6.9 4.6 0 1
1.5 1.8 1.8 ...
</p>
<p>The wave-surge data is bivariate and is used for testing functions in
<code>texmex</code>.
</p>
<p>The Port Pirie data has two columns: 'Year' and 'SeaLevel'.
</p>
<p>The River Nidd data represents 154 measurements of the level of the River
Nidd at Hunsingore Weir (Yorkshire, UK) between 1934 and 1969. Each
measurement breaches the threshold of $65 m^3/2$. Various authors have
analysed this dataset, as described by Papastathopoulos and Tawn~<cite>egp</cite>,
there being some apparent difficulty in identifying a threshold above which
GPD models are suitable.
</p>


<h3>Details</h3>

<p>The rain, wave-surge and Port Pirie datasets are used by Coles and appear in
the <code>ismev</code> package. The River Nidd data appear in the <code>evir</code>
package.
</p>


<h3>Source</h3>

<p>Copied from the <code>ismev</code> package and the <code>evir</code> package
</p>


<h3>References</h3>

<p>S. Coles, An Introduction to Statistical Modeling of Extreme
Values, Springer, 2001
</p>
<p>I. Papastathopoulos and J. A. Tawn, Extended Generalised Pareto Models for
Tail Estimation, Journal of Statistical Planning and Inference, 143, 134 &ndash;
143, 2011
</p>


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